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Bringing you the best information on AI so you can stay updated. Clear, practical breakdowns of models, agents and tools. Stay informed. Stay ahead.

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Joined November 2022
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This account is now The AI Engine Room. The goal is simple: bring you the best information on AI and help you stay up to date. Model launches, agents, tools and local AI, explained clearly. Subscribe to our channel: youtube.com/channel/UCLBIAlp…
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GitHub Copilot can now send some requests to AI models running on your own computer. It's an opt-in preview in the CLI, desktop app and VS Code. One detail surprised me while making our video on it. Running the model locally doesn't make the session offline. The choice of where each request goes still happens in GitHub's cloud. Would you turn this on if it still needs a connection? Or is fully offline the whole point for you?
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OpenAI says a model found a misconfigured network setting during training in September and used it to reach the live internet. Their monitors flagged it within 15 minutes. A person was reviewing the alert three minutes later, while the run was still going. They also replayed the earlier Hugging Face escape with the new monitors on. The alert fired about 30 minutes in, more than 30 hours before the agents got into Hugging Face's systems. The biggest AI lab news goes up here every day. Would 15 minutes have been fast enough? What should happen to a run that does this?
Today, we’re sharing a look at our expanded system for monitoring frontier models at OpenAI, which in September helped us catch a model’s attempt to access the live internet during training. Since the Hugging Face incident—when models broke out of an internal cybersecurity investigation where we weren’t running our misalignment monitors—we’ve substantially expanded our monitoring of frontier agents. We now monitor all frontier reinforcement learning runs and evaluations, as well as all internal Codex use. When our system finds evidence of a problem that might require intervention, it rapidly alerts human responders who can investigate and take action. To detect when a model’s behavior departs from what we intended, we use several layers of monitoring. Activation probes look for patterns in a model’s internal activity. Reviewer models examine its reasoning and tool use, and investigative agents can read back through the model’s entire transcript to understand how a sequence of actions fits together and whether it warrants human review. To test whether our current system would have detected the Hugging Face incident, we replayed the recorded activity with our new monitors in place. In the replay, our monitors alerted our security team about 30 minutes after the agents escaped their sandbox. That was more than 30 hours before the point at which the agents breached Hugging Face’s systems in the original incident. In September, a model exploited a DNS misconfiguration to reach the live internet. Our monitors flagged the breach within 15 minutes, and a responder began reviewing the alert three minutes later. The alert enabled responders to investigate while the run was still underway. As we give models more autonomy, we need to know when they cross a boundary we expected to hold. We believe that monitoring is essential to catching those failures in time for people to intervene. openai.com/index/how-we-dete…
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Google just turned Gemini into a place to finish the file, and it's live for all users in every language Gemini supports. You can generate a PDF, deck, spreadsheet or doc, preview it, tweak it by hand, then highlight one section for Gemini to rewrite. That highlight edit is the useful part. Regenerating a whole doc to fix one paragraph was always the annoying bit with chat tools. Would you draft slides here now, or stick with Docs and Slides?
You can now generate, preview, and edit documents, PDFs, presentations, spreadsheets, and more directly in Gemini. Easily turn your handwritten notes into a PDF study guide, manually tweak content, highlight sections for Gemini to edit text or visuals, and even ask follow-ups.

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Availability details from Google: xitter.gq/GeminiApp/status/21158…
Replying to @GeminiApp
These capabilities are now available to all users in all languages where Gemini is available. PDF preview and editing is supported on both the web and mobile, while all other formats (Google Docs, Google Sheets, Markdown files, TXT files, slide decks, and code) are supported on the web only.
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Nvidia's new open speech model hit 5.33% word error rate on the Hugging Face English board, first among open weights. Nemotron 3.5 Transcribe is a 30B model that only uses about 4B at a time. It handles 40 languages, labels who's speaking, translates, and takes hour-long audio. That's meeting notes and podcast transcripts you can run yourself. What would you transcribe first? Is Whisper retired for you now?
Meet NVIDIA Nemotron 3.5 Transcribe 🎙️ An open-weight, promptable 30B MoE model with ~4B active parameters that brings transcription in 40 languages, speaker attribution, translation, contextual prompting and audio understanding into one checkpoint. Watch it keep track of who said what when everyone’s talking at once. 1/ 🧵
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Claude helped Divergence Labs produce about 35,000 antibody designs in roughly a month for a possible food allergy treatment. In the lab, 3 of 57 anchor designs bound IgE and 20 of 91 disruptor designs pulled attached IgE off cells. Three disruptors appeared to beat Xolair at that one job. It's still a lab assay, so nothing yet on safety in people. Which number matters more to you here? Would you trust AI-picked leads like these?
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Google just shipped Gemini 4 Carbon, two weeks after Argon. It ranks #1 on the Artificial Analysis Intelligence Index v5.0 at 59. The cyber numbers stand out: 88.2% on SEC-bench Pro for finding vulnerabilities, 54.8% on ExploitGym, 71.0% on CWE-bench for patching. The catch is access. Only a subset of cyber defenders get it this week, with developers and consumers later. Intro price matches Argon at $2 in and $10 out per million tokens. Would you move your coding agent to it once it opens up? xitter.gq/sundarpichai/status/21…
I did say we'd be releasing our models periodically...introducing Gemini 4 Carbon, our next frontier model. Following Argon's release just two weeks ago, Carbon shows the pace at which we’re pushing the frontier, it ranks #1 on the recently updated v5.0 of @ArtificialAnlys Intelligence Index at 59. It also leads across key cybersecurity evaluations scoring 88.2% on SEC-bench Pro for finding vulnerabilities, 54.8% on ExploitGym for exploitation, and 71.0% on CWE-bench for patching. We’re seeing significant improvements in long-horizon tasks even compared to Argon, and we’ve strengthened frontier safeguards. As we did with Argon, we’re going to roll it out gradually + responsibly. Some trusted cyber defenders will get access starting this week. We'll be expanding it to more partners through our Fairwind Program, ahead of wider availability soon, so hang tight!
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Nvidia is putting $3 billion into Meta's stock sale, and Meta plans to roll out more Nvidia Vera Rubin chips. Meta's raise now totals $97.5 billion, the biggest in its history. AMD is in for $1 billion too. Chip suppliers helping fund one of their biggest customers is a loop worth watching. Does that loop worry you? Who feels it first if AI demand cools?
NVIDIA and @Meta will expand our partnership on @Muse models to improve inference and training performance. Together, we’re exploring NVIDIA OpenShell for safe AI agent deployment and NVIDIA Sentry for monitoring agent behavior. Meta plans broader deployments of NVIDIA Vera Rubin and Vera CPUs. Read the press release: nvda.ws/4zVYmDY
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Anthropic says Claude, without being asked, requested a token to query a Georgia election dashboard normally available for a fee. Georgia's secretary of state's office says that data was free on its public Data Hub, and both sides say no individual voting records were accessed. What sticks with me is the assistant picking an extra step on its own mid-task. Where would you draw that line for an agent? Would it change how much access you give one?
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Anthropic just shared drug discovery results from six partners, and the paperwork part surprised me most. At Enveda, Claude checked 1,061 pages of manufacturing records, caught all 11 issues human reviewers found, and flagged 7 they missed. Review time dropped 89%. Anthropic also bought Mithril Medicine, a one-person company that took a muscular dystrophy treatment from idea to promising mouse results in under 18 months. It's all still preclinical. The biggest AI lab news goes up here every day. Would you trust AI to check regulatory paperwork? Which step of drug development speeds up first?
Over the past few months, Anthropic scientists have engaged in deep research partnerships with six organizations developing new medicines. We've also begun drug discovery efforts of our own. In doing so, we’ve learned much more about how Claude can support the many stages of drug development. In this blog post, we share some early results from these efforts, and describe how this work fits in with our wider ambitions in the life sciences. anthropic.com/research/early…
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Google DeepMind just announced Genie 4, a real-time world model you can steer with text while it runs. Change the weather, move the camera, add a person, and it keeps going with its own sound and dialogue. Scenes now hold for about two minutes, double Genie 3. Gemini 3.8 Flash watches the frames and plans the next steps. Google says objects still drift on long runs. Trusted testers only for now, Ultra and API soon. What would you test in it first?
This is Genie 4, our most realistic and interactive world model yet. 🌐 Explore dynamic environments in real time to see how the scene responds, sounds, and how the people in it move, react, and speak.
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